Use of Structural Equation Modelling and Neural Network to Analyse Shared Parking Choice Behaviour

IF 0.8 4区工程技术 Q4 TRANSPORTATION SCIENCE & TECHNOLOGY

Promet-Traffic & Transportation Pub Date : 2023-10-30 DOI:10.7307/ptt.v35i5.209

Yi Zhu, Shuyan Chen, Ying Wu, Fengxiang Qiao, Yongfeng Ma

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引用次数: 0

Abstract

The shared parking mode represents a feasible solution to the persistent problem of parking scarcity in urban areas. This paper aims to examine the shared parking choice behaviours using a combination of structural equation modelling (SEM) and neural network, taking into account both the parking location characteristics and the travellers’ characteristics. Data were collected from a commercial district in Nanjing, China, through an online questionnaire survey covering 11 factors affecting shared parking choice. The method involved two steps: firstly, SEM was applied to examine the influence of these factors on shared parking choice. Following this, the seven factors with the strongest correlation to shared parking choice were used to train a neural network model for shared parking prediction. This SEM-informed model was found to outperform a neural network model trained on all eleven factors across precision, recall, accuracy, F1 and AUC metrics. The research concluded that the selected factors significantly influence shared parking choice, reinforcing the hypothesis regarding the importance of parking location and traveller characteristics. These findings provide valuable insights to support the effective implementation and promotion of shared parking.

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基于结构方程模型和神经网络的共享停车选择行为分析

共享停车模式是解决城市长期存在的停车稀缺问题的一种可行方案。本文将结构方程模型与神经网络相结合，在考虑停车区位特征和出行者特征的情况下，对共享停车选择行为进行研究。数据来自中国南京的一个商业区，通过在线问卷调查收集了11个影响共享停车选择的因素。该方法分为两个步骤:首先，利用扫描电镜分析这些因素对共享停车选择的影响;在此基础上，利用与共享车位选择相关性最强的7个因素，训练神经网络模型进行共享车位预测。研究发现，这种基于sem的模型优于在精度、召回率、准确性、F1和AUC指标等所有11个因素上训练的神经网络模型。研究结果表明，选择的因素显著影响共享停车选择，强化了停车位置和出行者特征重要性的假设。这些研究结果为有效推行和推广共享泊车服务提供了宝贵的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Promet-Traffic & Transportation 工程技术-运输科技

CiteScore

1.90

自引率

20.00%

发文量

审稿时长

3 months

期刊介绍： This scientific journal publishes scientific papers in the area of technical sciences, field of transport and traffic technology. The basic guidelines of the journal, which support the mission - promotion of transport science, are: relevancy of published papers and reviewer competency, established identity in the print and publishing profile, as well as other formal and informal details. The journal organisation consists of the Editorial Board, Editors, Reviewer Selection Committee and the Scientific Advisory Committee. The received papers are subject to peer review in accordance with the recommendations for international scientific journals. The papers published in the journal are placed in sections which explain their focus in more detail. The sections are: transportation economy, information and communication technology, intelligent transport systems, human-transport interaction, intermodal transport, education in traffic and transport, traffic planning, traffic and environment (ecology), traffic on motorways, traffic in the cities, transport and sustainable development, traffic and space, traffic infrastructure, traffic policy, transport engineering, transport law, safety and security in traffic, transport logistics, transport technology, transport telematics, internal transport, traffic management, science in traffic and transport, traffic engineering, transport in emergency situations, swarm intelligence in transportation engineering. The Journal also publishes information not subject to review, and classified under the following headings: book and other reviews, symposia, conferences and exhibitions, scientific cooperation, anniversaries, portraits, bibliographies, publisher information, news, etc.